1. Field
The present invention relates to an apparatus and method for updating a named entity dictionary or a mining rule database using the named entity dictionary and a mining rule combined with an ontology schema, in which the named entity dictionary or the mining rule database is updated by searching for a named entity or a mining rule combined with the ontology schema using the entity dictionary and the mining rule database stored in advance, estimating a named entity using the mining rule if a matching named entity is not searched, and estimating a mining rule using the named entity if a mining rule is not searched.
2. Description of the Related Art
Recently, data models using ontology are spotlighted in relation to studies on semantic webs. The ontology is a working model of entities and interactions existing in a specific domain. That is, the ontology conceptualizes and specifies knowledge in the specific domain and can be defined as a network or a graph having a relationship among the concepts used in the domain.
The ontology is constructed by obtaining knowledge related to constitutional elements of the ontology to be constructed in the ontology, such as concepts, attributes of the concepts, and connection relations among the concepts, from documents related to a specific field, defining concepts and attributes, and setting relations among the concepts.
In addition, in order to give meanings to web resources, the ontology can be expressed as a resource description framework (RDF) which is a 3-dimensional structure of resource, attribute, and attribute value.
The RDF is constructed as a concept of resource, property, and statement. All things of an inputted document are expressed as resources, and the RDF can express properties of each resource and relations of the resource with the other resources.
An RDF network can be constructed by detecting named entities from the inputted document and converting the named entities into corresponding RDF triples using mining rules.
The named entity is a word or a set of words that can be classified, such as a name of a person or an organization, a title of music, a name of broadcasting, or a name of a place, and the mining rule is configured with a mining pattern and an RDF triple that can be obtained from the mining pattern.
Detection of a named entity is a field of study that is very important in a knowledge learning field, particularly related to a voice language, and a lot of algorithms are proposed for detection of named entities.
A method based on a dictionary is the most fundamental method for detecting named entities, in which a named entity is detected by extracting a word or a set of words determined as a named entity from the inputted sentence and comparing the extracted word or set of words with a named entity stored in a previously stored named entity dictionary.
In addition, a method of converting a named entity into an RDF triple using a mining rule is a method of searching for a matching mining pattern from a previously stored mining rule database and converting the mining rule into a corresponding RDF triple.
However, the named entities or the mining rules are not fixed along a time axis, but have a characteristic of being newly generated according to a society, culture, or the like and disappeared with time, and thus the named entities and the mining rules need to be updated.